Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches
The development of multibeam echosounders (MBES) as a seabed mapping tool has resulted in the widespread uptake of backscatter intensity as an indicator of seabed substrate properties. Though increasingly common, the lack of standard calibration and the characteristics of individual sonars generally...
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doaj-bd09013eea27498ea3f8bcfe186fad5d2020-11-25T01:14:52ZengMDPI AGRemote Sensing2072-42922020-02-0112460110.3390/rs12040601rs12040601Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift ApproachesBenjamin Misiuk0Craig J. Brown1Katleen Robert2Myriam Lacharité3School of Ocean Technology, Fisheries and Marine Institute of Memorial University of Newfoundland, St. John’s, NL A1C 5R3, CanadaDepartment of Oceanography, Dalhousie University, Halifax, NS B5H 4R2, CanadaSchool of Ocean Technology, Fisheries and Marine Institute of Memorial University of Newfoundland, St. John’s, NL A1C 5R3, CanadaInstitute for Marine and Antarctic Studies, University of Tasmania, Hobart 7053, AustraliaThe development of multibeam echosounders (MBES) as a seabed mapping tool has resulted in the widespread uptake of backscatter intensity as an indicator of seabed substrate properties. Though increasingly common, the lack of standard calibration and the characteristics of individual sonars generally produce backscatter measurements that are relative to a given survey, presenting major challenges for seabed mapping in areas that comprise multiple MBES surveys. Here, we explore methods for backscatter dataset harmonization that leverage areas of mutual overlap between surveys for relative statistical calibration—referred to as “bulk shift” approaches. We use three multispectral MBES datasets to simulate the harmonization of backscatter collected over multiple years, and using multiple operating frequencies. Results suggest that relatively simple statistical models are adequate for bulk shift harmonization procedures, and that more flexible approaches may produce inconsistent results that risk statistical overfitting. While harmonizing datasets collected using the same operating frequency from separate surveys is generally feasible given reasonable temporal limitations, results suggest that the success at harmonizing datasets of different operating frequencies partly depends on the extent to which the frequencies differ. We recommend approaches and diagnostics for ensuring the quality of harmonized backscatter mosaics, and provide an R function for implementing the methods presented here.https://www.mdpi.com/2072-4292/12/4/601backscattermultispectralmultibeamechosounderseabed mappingbenthichabitat mapping |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Benjamin Misiuk Craig J. Brown Katleen Robert Myriam Lacharité |
spellingShingle |
Benjamin Misiuk Craig J. Brown Katleen Robert Myriam Lacharité Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches Remote Sensing backscatter multispectral multibeam echosounder seabed mapping benthic habitat mapping |
author_facet |
Benjamin Misiuk Craig J. Brown Katleen Robert Myriam Lacharité |
author_sort |
Benjamin Misiuk |
title |
Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches |
title_short |
Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches |
title_full |
Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches |
title_fullStr |
Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches |
title_full_unstemmed |
Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches |
title_sort |
harmonizing multi-source sonar backscatter datasets for seabed mapping using bulk shift approaches |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2020-02-01 |
description |
The development of multibeam echosounders (MBES) as a seabed mapping tool has resulted in the widespread uptake of backscatter intensity as an indicator of seabed substrate properties. Though increasingly common, the lack of standard calibration and the characteristics of individual sonars generally produce backscatter measurements that are relative to a given survey, presenting major challenges for seabed mapping in areas that comprise multiple MBES surveys. Here, we explore methods for backscatter dataset harmonization that leverage areas of mutual overlap between surveys for relative statistical calibration—referred to as “bulk shift” approaches. We use three multispectral MBES datasets to simulate the harmonization of backscatter collected over multiple years, and using multiple operating frequencies. Results suggest that relatively simple statistical models are adequate for bulk shift harmonization procedures, and that more flexible approaches may produce inconsistent results that risk statistical overfitting. While harmonizing datasets collected using the same operating frequency from separate surveys is generally feasible given reasonable temporal limitations, results suggest that the success at harmonizing datasets of different operating frequencies partly depends on the extent to which the frequencies differ. We recommend approaches and diagnostics for ensuring the quality of harmonized backscatter mosaics, and provide an R function for implementing the methods presented here. |
topic |
backscatter multispectral multibeam echosounder seabed mapping benthic habitat mapping |
url |
https://www.mdpi.com/2072-4292/12/4/601 |
work_keys_str_mv |
AT benjaminmisiuk harmonizingmultisourcesonarbackscatterdatasetsforseabedmappingusingbulkshiftapproaches AT craigjbrown harmonizingmultisourcesonarbackscatterdatasetsforseabedmappingusingbulkshiftapproaches AT katleenrobert harmonizingmultisourcesonarbackscatterdatasetsforseabedmappingusingbulkshiftapproaches AT myriamlacharite harmonizingmultisourcesonarbackscatterdatasetsforseabedmappingusingbulkshiftapproaches |
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